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Finite Impulse Response Errors-in-Variables System Identification Utilizing Approximated Likelihood and Gaussian Mixture Models.

, , , , and . IEEE Access, (2023)

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A Bayesian approach to sparse channel estimation in OFDM systems., , and . CoRR, (2013)An optimization-based algorithm for model selection using an approximation of Akaike's Information Criterion., , and . AuCC, page 217-220. IEEE, (2016)A novel approach to model error modelling using the expectation-maximization algorithm., , , and . CDC, page 7327-7332. IEEE, (2012)EM-Based Maximum-Likelihood Channel Estimation in Multicarrier Systems With Phase Distortion., , , and . IEEE Trans. Veh. Technol., 62 (1): 152-160 (2013)Information criterion-based channel estimation in OFDM systems with time and frequency offset., , and . LATINCOM, page 1-5. IEEE, (2016)An EM-based estimation algorithm for a class of systems promoting sparsity., , and . ECC, page 2398-2403. IEEE, (2013)Sparse logistic regression utilizing cardinality constraints and information criteria., , , , and . CCA, page 798-803. IEEE, (2016)A map approach for ℓq-norm regularized sparse parameter estimation using the EM algorithm., , , and . MLSP, page 1-6. IEEE, (2015)Concept Maps: Integrating Knowledge and Information Visualization., , , , , , , and . Knowledge and Information Visualization, volume 3426 of Lecture Notes in Computer Science, page 205-219. Springer, (2005)Finite Impulse Response Errors-in-Variables System Identification Utilizing Approximated Likelihood and Gaussian Mixture Models., , , , and . IEEE Access, (2023)